Interpretive Summary:
Contamination of corn grain with aflatoxin, which is produced by the fungus Aspergillus flavus, is a serious health hazard to humans, livestock, and pets. Growing corn hybrids with genetic resistance to aflatoxin accumulation in the grain is generally considered a highly desirable method of reducing aflatoxin contamination. This investigation was undertaken to identify chromosomal regions of an aflatoxin-resistant inbred line, Mp313E, that are associated with the inheritance of resistance to aflatoxin contamination. Progeny derived from a cross between Mp313E and a susceptible inbred line were inoculated with A. flavus and evaluated for percentage of infected kernels, and DNA profiles were also determined for the progeny. Molecular markers associated with resistance to A. flavus infection were determined by two methods. Five chromosomal, or genomic regions, associated with resistance to A. flavus infection were identified. The use of these molecular markers will facilitate development of aflatoxin-resistant corn hybrids.

Technical Abstract:
Aflatoxin contamination of maize (Zea mays L.) grain caused by Aspergillus flavus is a serious health hazard to animals and humans. Resistance to infection by A. flavus is poorly understood. The objectives of this investigation were to identify potential candidate markers associated with resistance in maize kernels and to A. flavus using a mapping population derived from a cross between Mp313E (resistant) and SC212m (susceptible) inbred lines. The parents, F1, and F2 plants were planted in the field in 2005. Each F2 was selfed to produce F2:3 seed. Selfed seeds from parents, F1, and F2 plants were challenged with A. flavus conidial suspension and incubated using a medium-free method. Percent kernels uninfected (PKU) were recorded. A linkage map was constructed with JoinMap 3.0 using DNA profiles of all F2 individuals produced from amplified fragment length polymorphism (AFLP) and target region amplification polymorphism (TRAP) markers. Interval mapping and multiple-QTL model (MQM) mapping analyses were performed using MapQTL 4.0 software. Three marker-QTL associations were observed for log-transformed PKU. Potential markers associated with this trait were also identified via discriminant analysis (DA). The markers identified via DA pointed to the same genomic regions as identified via the QTL mapping strategy. For log-transformed NPG, five marker-QTL associations were detected. One QTL was associated with a TRAP marker. The DA confirmed the existence of three QTL.